R sqaured And Adjusted R squared Machine Learning In Hindi|Krish Naik Hindi

Adjusted R-squared can provide a more precise view of that correlation by also taking into account how many independent variables are added to a particular model
R-squared is expressed as a percentage between 0 and 100, with 100 signaling perfect correlation and zero no correlation at all.
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[@MuhammadWahab-jt6ly]

love the way of teaching ......
Algorithm must should viral you

[@SiddharthDeo]

Awesome gem content never stop making videos we will always support you.
Thanks Krrish

[@mayanktiwari2498]

Thank you Krish for simplifying this topic!

[@rubayetalam8759]

PLEASE KEEP UPLOADING MORE CLASSES. BEST ML COURSE THEY ARE!

[@MuhammadWahab-jt6ly]

Amazing knowledge able content 😍

[@abdullahbinmohammed88]

Excellent description sir

[@083-cse-sameerkhan3]

GUYS R^2 formula is R^2=1-(SSE/SST) correct it mistakenly sir written it wrong

[@endsemister]

great video sir....

[@divyakarlapudi]

Thank you so much for thus explanation :)

[@tavishimehta4848]

Thank you sir

[@Sahilkumar-dd6de]

thanku so much sir love from gndu amritsar

[@DrChandrabhanPatel]

nice described

[@prabinsharma1169]

Krish sir I need K means clustering algorithm video with full explanation in easy way please make video in this algorithm plzz plz plz plz plz plz

[@SohamNimale]

10:43 I did not understand why if p increases, the value should decrease. There is a 1 - ... right, so shouldn't the overall value decrease.

[@kunalkhare8340]

sir please course ki videos jldi jldi laiye

[@HamsterKombat0502]

Sir, how does the machine knows whether it is useful parameter or not
in case of adjusted r2 if we add useful parameter also it decreases sir please explain on this

[@darksoul2734]

which software tool use you sir ?

[@Ayushi118]

Sir I am not able to get this point ki how the P = 3 will make adjusted R² 70 % when gender is taken as 3rd P and it will become 74% when location will be taken as 3rd P... mathematically P= 3 will give same result na!

[@nishitasinha8144]

Sir, how is the value of Adjusted R squared decreasing on addition of any feature? Because the model doesn't know if the added feature is important or not. What happens if even for the second time, the added feature is an important feature w.r.t the target variable? Will the adjusted R2 still decrease or increase?

[@JimsChacko]

It doesn't matter if the feature is important or not. Adjusted R2 will always be less or equal to R2 since we are taking no of independent variables at the bottom. So if you add more features the adjusted r2 will keep on decreasing rather than increasing.

[@techbinay]

you mean if feature is important it will include in r2 formula but it's not important will include in adjusted r2 formula @@JimsChacko